**IMFDataPy** Table of Contents

IMFDataPy

A package for data discovery and extraction from the International Monetary Fund (IMF)! This repository contains Python source code and Jupyter notebooks with examples on how to extract data from the IMF.

Installation

    $ pip install imfdatapy

Usage

IMFDataPy can be used to search through and extract data as follows. The examples below show how to search through the IFS (International Financial Statistics) and BOP (Balance of Payments) using serach_terms and download all the data with matching economic indicator names.

from imfdatapy.imf import *
ifs = IFS(search_terms=["gross domestic product, real"], countries=["US"], period='Q',
start_date="2000", end_date="2022")
df = ifs.download_data()

bop = BOP(search_terms=["current account, total, credit"], countries=["US"], period='Q',
start_date="2000", end_date="2022")
df = bop.download_data()

Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

imfdatapy was created by Sou-Cheng T. Choi and Irina Klein, Illinois Institute of Technology. It is licensed under the terms of the Apache License, v2.0.

With regard to the terms for using IMF data, please refer to IMF’s Copyright and Usage and pay special attention to the section SPECIAL TERMS AND CONDITIONS PERTAINING TO THE USE OF DATA.

Credits

imfdatapy was created with cookiecutter and the py-pkgs-cookiecutter template.

Changelog

v0.1.5 (26/11/2022)

  • Resolve dependecies issue and mkdir before pandas.to_csv.

v0.1.1 (25/11/2022)

  • Change source code to OO version for search and data extraction.

v0.1.0 (24/11/2022)

  • First release of IMFDataPy! Reserve name on PyPi.

Contributing

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

Types of Contributions

Report Bugs

If you are reporting a bug, please include:

  • Your operating system name and version.

  • Any details about your local setup that might be helpful in troubleshooting.

  • Detailed steps to reproduce the bug.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with “bug” and “help wanted” is open to whoever wants to implement it.

Implement Features

Look through the GitHub issues for features. Anything tagged with “enhancement” and “help wanted” is open to whoever wants to implement it.

Write Documentation

You can never have enough documentation! Please feel free to contribute to any part of the documentation, such as the official docs, docstrings, or even on the web in blog posts, articles, and such.

Submit Feedback

If you are proposing a feature:

  • Explain in detail how it would work.

  • Keep the scope as narrow as possible, to make it easier to implement.

  • Remember that this is a volunteer-driven project, and that contributions are welcome :)

Get Started!

Ready to contribute? Here’s how to set up IMFDataPy for local development.

  1. Download a copy of IMFDataPy locally.

$ git clone https://github.com/Economic-and-Financial-Data-Discovery/imfdatapy.git
$	cd imfdatapy
$	git checkout develop

  1. Install IMFDataPy using conda:

    $ conda env create --file environment.yml
$ conda activate imfdatapy
$ jupyter nbextensions_configurator enable --user
$ python -m ipykernel install --user --name=imfdatapy
$ pip install -e .

  2. Use git (or similar) to create a branch for local development and make your changes:

    $ git checkout -b name-of-your-bugfix-or-feature

  3. When you’re done making changes, check that your changes conform to any code formatting requirements and pass any tests.

  4. Commit your changes and open a pull request.

Pull Request Guidelines

Before you submit a pull request, check that it meets these guidelines:

  1. The pull request should include additional tests if appropriate.

  2. If the pull request adds functionality, the docs should be updated.

  3. The pull request should work for all currently supported operating systems and versions of Python.

Code of Conduct

Please note that the IMFDataPy project is released with a Code of Conduct. By contributing to this project you agree to abide by its terms.

Code of Conduct

Our Pledge

In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.

Our Standards

Examples of behavior that contributes to creating a positive environment include:

  • Using welcoming and inclusive language

  • Being respectful of differing viewpoints and experiences

  • Gracefully accepting constructive criticism

  • Focusing on what is best for the community

  • Showing empathy towards other community members

Examples of unacceptable behavior by participants include:

  • The use of sexualized language or imagery and unwelcome sexual attention or advances

  • Trolling, insulting/derogatory comments, and personal or political attacks

  • Public or private harassment

  • Publishing others’ private information, such as a physical or electronic address, without explicit permission

  • Other conduct which could reasonably be considered inappropriate in a professional setting

Our Responsibilities

Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior.

Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful.

Scope

This Code of Conduct applies both within project spaces and in public spaces when an individual is representing the project or its community. Examples of representing a project or community include using an official project e-mail address, posting via an official social media account, or acting as an appointed representative at an online or offline event. Representation of a project may be further defined and clarified by project maintainers.

Enforcement

Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by contacting the project team. The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately.

Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project’s leadership.

Attribution

This Code of Conduct is adapted from the Contributor Covenant homepage, version 1.4.

Demos

IMFDataPy Architecture

from IPython.display import IFrame

IFrame("mermaid/imfdatapy_architecture_state_diagram.html", width=500, height=400)

IFrame("mermaid/imfdatapy_architecture_sequence_diagram.html", width=500, height=500)

IFrame("mermaid/imfdatapy_architecture_class_diagram.html", width=500, height=400)